Learn to detect multiple objects in real time using the YOLO algorithm. Understand bounding boxes, confidence scores, and model training. Build applications for security, traffic monitoring, and automation. Optimize detection speed and accuracy. Deploy production-ready object detection models.
Master enterprise-grade AI engineering using production-ready architectures, distributed model training, GPU acceleration, transformer networks, vector embeddings, and scalable inference pipelines. Implement TensorFlow, PyTorch, Hugging Face, CUDA, ONNX Runtime, TensorRT, and modern MLOps workflows. Design high-performance solutions with RAG, semantic search, FAISS, Pinecone, LangChain, Kubernetes, and cloud-native deployment strategies. Develop optimized, production-ready AI applications following industry best practices for scalability, observability, security, and performance.
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